Abstract
Point Set Registration (PSR) algorithms have very different underlying theoretical models to define a process that calculates the alignment solution between two point clouds. The selection of a particular PSR algorithm can be based on the efficiency (time to compute the alignment) and accuracy (a measure of error using the estimated alignment). In our specific context, previous work used a CPD algorithm to detect and quantify change in spatiotemporal datasets composed of moving and shape-changing objects represented by a sequence of time stamped 2D polygon boundaries. Though the results were promising, we question if the selection of a particular PSR algorithm influences the results of detection and quantification of change. In this work we review and compare several PSR algorithms, characterize test datasets and used metrics, and perform tests for the selected datasets. The results show pyCPD and cyCPD implementations of CPD to be good alternatives and that BCPD can have potential to be yet another alternative. The results also show that detection and quantification accuracy change for some of the tested PSR implementations.

Abstract
In recent years, there has been growing interest in digital twins (or virtual representations) of the environment. Programs in the European Union and the UN are investing in digital twins, particularly those of the ocean (DTOs). While citizen science has been mentioned as a potential data source for digital twins, the full potential of citizen science in this context has yet to be fully realised. The Iliad project (https://ocean-twin.eu), funded by the European Commission, is developing a comprehensive set of digital twins of the oceans which are interoperable, data-intensive, and cost-effective. The project (2022-2025) brings together over 50 partners to demonstrate the technologies and methodologies required to develop DTOs. Citizen science and engagement play a pivotal role in the project, with the following goals: (a) exploring the potential for citizen science to contribute to digital twins of the oceans; (b) demonstrating how citizen scientists (and society more broadly) can benefit from digital twins. The Iliad team is currently working on over 20 separate digital twins of the oceans that fall into two primary categories: (i) environmental and ecological digital twins; (ii) engineering and industrial digital twins. Using the Iliad DTOs as case studies, lessons learned for citizen science are presented from the development of each digital twin.

Abstract
Europe's position in the current cloud market needs to be improved. This market is currently dominated by non-European players by 75%, shaping the way that Europe is deploying and using cloud services. Although these players are bound to laws and regulations of foreign powers, such as PR China and USA, generating legitimate concerns for the EU, its businesses and citizens. EU's digital future resides on having installed secure, high-quality data processing capacity. This can only be offered by cloud services both centrally and at the edge. In this context NOUS's ambition is completely in line with the European Strategy for data as aims to create the foundations for a European Cloud Service which exploits the HPC network and tackles specific-to-the-EU-economy requirements as well as leverages different data spaces (Mobility, Energy, Green Deal and Manufacturing).

Abstract
This paper presents a solution for visualizing oil spills at sea by combining satellite data with virtual choreographies. The system enables dynamic, interactive visualization of oil slicks, reflecting their shape, movement, and interaction with environmental factors like currents and wind. High resolution geospatial data supports a multiplatform experience with aerial and underwater perspectives. This approach promotes independence, interoperability, and multiplatform compatibility in environmental disaster monitoring. The results validate virtual choreographies as effective tools for immersive exploration and analysis, offering structured data narratives beyond passive visualization especially valuable for mixed reality applications.

Abstract
In recent years, the development of Decision Support Systems (DSS) has played an instrumental role in the advancement of offshore renewable energy projects, particularly within the blue energy sector. Notwithstanding the technological advancements that have been made, the acceleration of such projects continues to be impeded by significant obstacles related to stakeholder engagement, feasibility assessment, and policy compliance. The objective of this study is to propose a design for a DSS for accelerating the construction of blue offshore energy platforms. This is to address the aforementioned challenges by integrating insights from stakeholder feedback and innovation trends. A participatory action study was conducted through a workshop with a diverse group of experts (n=20), including policymakers, practitioners, researchers, and public entities involved in offshore energy projects. The evaluation facilitated the determination of the DSS's efficacy in addressing user requirements and the identification of areas for enhancement. This study proposes a model for integrating stakeholder insights into technological solutions for offshore energy installations, thus offers significant contributions to the domain of sustainable blue energy development.

Abstract
Digital Twins (DTs) for the ocean are rapidly emerging as essential tools for understanding, forecasting, and managing environmental phenomena. However, most existing DT visualization solutions are tightly coupled to specific platforms and lack semantic coherence and interoperability-challenges that are particularly critical in federated and distributed DT systems. Furthermore, visualizing dynamic and spatio-temporal behaviors, such as oil spills, across multiple rendering environments remains a complex, platform-dependent task. In this paper, we present VChor, a domain-agnostic virtual choreography framework designed to address these limitations. Our approach integrates model-driven engineering, semantic web technologies, and platform-independent representations to support the declarative specification of behaviors and visual mappings. A single VChor instance describes spatio-temporal dynamics and associated actions, and can be interpreted by multiple visualization engines (e.g., Unity3D and CesiumJS) without the need for code recompilation or platform-specific programming. We demonstrate our approach through a real-world oil spill monitoring use case, developed in the context of the ILIAD H2020 project, and encapsulated within a modular Application Package. This package automates the generation, validation, and transformation of virtual choreographies from raw data to platform-specific outputs. The framework promotes interoperability, reusability, and scalability, while supporting FAIR principles in environmental Digital Twin workflows. The findings highlight VChor's potential to streamline scenario modeling, enable cross-platform visualization, and support decision-makers with accurate, flexible, and reusable visual representations of ocean dynamics.